Privacy Preservation in Federated Learning: An insightful survey from the GDPR Perspective
Authors: Nguyen Truong, Kai Sun, Siyao Wang, Florian Guitton, Yike Guo | Published: 2020-11-10 | Updated: 2021-03-18
ポイズニング
DualNet: Locate Then Detect Effective Payload with Deep Attention Network
Authors: Shiyi Yang, Peilun Wu, Hui Guo | Published: 2020-10-23
VenoMave: Targeted Poisoning Against Speech Recognition
Authors: Hojjat Aghakhani, Lea Schönherr, Thorsten Eisenhofer, Dorothea Kolossa, Thorsten Holz, Christopher Kruegel, Giovanni Vigna | Published: 2020-10-21 | Updated: 2023-04-20
Mitigating Sybil Attacks on Differential Privacy based Federated Learning
Authors: Yupeng Jiang, Yong Li, Yipeng Zhou, Xi Zheng | Published: 2020-10-20
A Survey of Machine Learning Techniques in Adversarial Image Forensics
Authors: Ehsan Nowroozi, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond Choo | Published: 2020-10-19
GOAT: GPU Outsourcing of Deep Learning Training With Asynchronous Probabilistic Integrity Verification Inside Trusted Execution Environment
Authors: Aref Asvadishirehjini, Murat Kantarcioglu, Bradley Malin | Published: 2020-10-17
BlockFLA: Accountable Federated Learning via Hybrid Blockchain Architecture
Authors: Harsh Bimal Desai, Mustafa Safa Ozdayi, Murat Kantarcioglu | Published: 2020-10-14
How Does Mixup Help With Robustness and Generalization?
Authors: Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou | Published: 2020-10-09 | Updated: 2021-03-17
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Authors: Sven Gowal, Chongli Qin, Jonathan Uesato, Timothy Mann, Pushmeet Kohli | Published: 2020-10-07 | Updated: 2021-03-30
Understanding Catastrophic Overfitting in Single-step Adversarial Training
Authors: Hoki Kim, Woojin Lee, Jaewook Lee | Published: 2020-10-05 | Updated: 2020-12-15